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Encyclopedia of Systems and Control pp 870–876Cite as

Nonlinear Filters

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Abstract

Nonlinear filters estimate the state of dynamical systems given noisy measurements related to the state vector. In theory, such filters can provide optimal estimation accuracy for nonlinear measurements with nonlinear dynamics and non-Gaussian noise. However, in practice, the actual performance of nonlinear filters is limited by the curse of dimensionality. There are many different types of nonlinear filters, including the extended Kalman filter, the unscented Kalman filter, and particle filters.

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Author information

Authors and Affiliations

  1. Raytheon Company, Woburn, MA, USA

    Frederick E. Daum

Authors
  1. Frederick E. Daum
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Editor information

Editors and Affiliations

  1. Mechanical Engineering, Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Honeywell Automation and Control Solutions, Golden Valley, MN, USA

    Tariq Samad

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© 2015 Springer-Verlag London

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Daum, F.E. (2015). Nonlinear Filters. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5058-9_63

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